Yazar "Catak, Muammer" seçeneğine göre listele

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    Conflict distance-based variable precision Pythagorean fuzzy rough set in Pythagorean fuzzy decision systems with applications in decision making
    (Int Scientific Research Publications, 2024) Sahoo, Lakshminarayan; Guchhait, Sanchita; Allahviranloo, Tofigh; Kumar, Jambi Ratna Raja; Tarambale, Manoj Ramesh; Catak, Muammer
    Real-life decision-making problems are hard to handle by any single uncertainty method because of the complex and uncertain nature of the physical world and the human limitations in understanding it. Therefore, we naturally consider combining the benefits of various uncertainty theories to create a more effective hybrid soft decision-making method. Based on this idea, we use the variable precision rough sets (VPRSs) and Pythagorean fuzzy sets approach to build a new Pythagorean fuzzy rough set (PFRS) model. Since the information system is Pythagorean fuzzy, we use the Pythagorean fuzzy similarity measure to define the new type of distance based on conflict. Then, we merge this notion with the VPRSs to form a variable precision PFRS model and study its properties. We also propose an algorithm for attribute reduction based on this model and apply it to a case study to test its feasibility and performance. The results demonstrate that our model enhances the classification capability of previous models, and it achieves accurate classification by deriving the decision rules.
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    A discrete heuristic algorithm with swarm and evolutionary features for data replication problem in distributed systems
    (Springer London Ltd, 2023) Arasteh, Bahman; Allahviranloo, Tofigh; Funes, Peri; Torkamanian-Afshar, Mahsa; Khari, Manju; Catak, Muammer
    Availability and accessibility of data objects in a reasonable time is a main issue in distributed systems like cloud computing services. As a result, the reduction of data-related operation times in distributed systems such as data read/write has become a major challenge in the development of these systems. In this regard, replicating the data objects on different servers is one commonly used technique. In general, replica placement plays an essential role in the efficiency of distributed systems and can be implemented statically or dynamically. Estimation of the minimum number of data replicas and the optimal placement of the replicas is an NP-complete optimization problem. Hence, different heuristic algorithms have been proposed for optimal replica placement in distributed systems. Reducing data processing costs as well as the number of replicas, and increasing the reliability of the replica placement algorithms are the main goals of this research. This paper presents a discrete and swarm-evolutionary method using a combination of shuffle-frog leaping and genetic algorithms to data-replica placement problems in distributed systems. The experiments on the standard dataset show that the proposed method reduces data access time by up to 30% with about 14 replicas; whereas the generated replicas by the GA and ACO are, respectively, 24 and 30. The average reduction in data access time by GA and ACO 21% and 18% which shows less efficiency than the SFLA-GA algorithm. Regarding the results, the SFLA-GA converges on the optimal solution before the 10th iteration, which shows the higher performance of the proposed method. Furthermore, the standard deviation among the results obtained by the proposed method on several runs is about 0.029, which is lower than other algorithms. Additionally, the proposed method has a higher success rate than other algorithms in the replica placement problem.
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    Fuzzy Laplace transform method for a fractional fuzzy economic model based on market equilibrium
    (Elsevier Science Inc, 2024) Babakordi, Fatemeh; Allahviranloo, Tofigh; Shahriari, M. R.; Catak, Muammer
    Fuzzy fractional models are of interest because they are very effective in describing real -world problems, but the analytical investigation of these models is often complex. Therefore, presenting a practical method for the analytical solution of these models is of particular importance. Hence, in this paper, first, the Laplace transform of the fuzzy ABC fractional derivative and its properties are introduced using the strongly generalized Hukuhara differentiability concept, and an analytical method for solving the fuzzy ABC fractional differential equation based on the Laplace transform is proposed. In the following, to show the comprehensiveness and appropriateness of the method, since the parameters are imprecise and ambiguous in economic problems, the price adjustment equation is modeled in the form of a fuzzy ABC fractional differential equation using the fuzzy ABC fractional derivative, and the fuzzy price for the adjustment equation is obtained using the proposed analytical fuzzy price. Finally, the effectiveness of the proposed approach is demonstrated with numerical examples.